Health Psychology
2015, Vol. 34, No. 9, 887– 895
© 2015 American Psychological Association
0278-6133/15/$12.00 http://dx.doi.org/10.1037/hea0000209
A Life-Span Behavioral Mechanism Relating Childhood Conscientiousness
to Adult Clinical Health
Sarah E. Hampson, Grant W. Edmonds,
and Lewis R. Goldberg
Joan P. Dubanoski and Teresa A. Hillier
Kaiser Permanente Center for Health Research Hawaii,
Honolulu, Hawaii
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Oregon Research Institute, Eugene, Oregon
Objective: To investigate a life-span health-behavior mechanism relating childhood personality to adult
clinical health. Methods: Childhood Big Five personality traits at mean age 10, adult Big Five personality
traits, adult clinically assessed dysregulation at mean age 51 (a summary of dysregulated blood glucose,
blood pressure, and lipids), and a retrospective, cumulative measure of life-span health-damaging
behavior (lifetime smoking, physical inactivity, and body mass index from age 20) were assessed in the
Hawaii Personality and Health Cohort (N ⫽ 759). Structural equation modeling was used to test the
conceptual model with direct and indirect paths from a childhood Conscientiousness factor to an adult
Conscientiousness factor, life-span health-damaging behaviors, educational attainment, adult cognitive
ability, and adult clinical health. Results: For both men and women, childhood Conscientiousness
influenced health-damaging behaviors through educational attainment, and life-span health-damaging
behaviors predicted dysregulation. Childhood Conscientiousness predicted adult Conscientiousness,
which did not predict any other variables in the model. For men, childhood Conscientiousness predicted
dysregulation through educational attainment and health-damaging behaviors. For women, childhood
Conscientiousness predicted dysregulation through educational attainment and adult cognitive ability.
Conclusions: Assessing cumulative life-span health behaviors is a novel approach to the study of
health-behavior mechanisms. Childhood Conscientiousness appears to influence health assessed more
than 40 years later through complex processes involving educational attainment, cognitive ability, and the
accumulated effects of health behaviors, but not adult Conscientiousness.
Keywords: childhood personality, clinical health, health behaviors, educational attainment, cognitive
ability
Supplemental materials: http://dx.doi.org/10.1037/hea0000209.supp
(Hampson, Edmonds, Goldberg, Dubanoski, & Hillier, 2013; Moffitt et al., 2011). Life-span personality-health research is now
focused on identifying mechanisms to account for these long-term
associations between childhood personality and adult health outcomes (Friedman & Kern, 2014). Ideally, this kind of research uses
longitudinal samples that have been assessed from childhood to
adulthood on appropriate measures of personality, health, and
potential mediating mechanisms. However, such studies are exceedingly rare. The current study contributes to this sparse literature by examining whether a retrospective report of cumulative
health behaviors performed over substantial periods of the life
span explain some portion of the association between childhood
personality and clinically assessed health status more than 40 years
later.
Of the several mechanisms proposed to account for the effects
of personality on later health outcomes (Friedman, 2000; Hampson
& Friedman, 2008; Smith, 2006), health-behavior models have so
far proved to be the most compelling and suggest potential opportunities for intervention. Health-behavior models propose that personality traits influence the performance of health-damaging and
health-enhancing behaviors, which are risk and protective factors,
respectively, for the leading causes of morbidity and mortality in
the United States (Mokdad, Marks, Stroup, & Gerberding, 2004;
Substantial evidence has accumulated to demonstrate that the
Big Five personality traits measured in adulthood (Extraversion,
Agreeableness, Conscientiousness, Emotional Stability, and Intellect/Openness) are associated prospectively with health status and
mortality (Bogg & Roberts, 2013; Jokela et al., 2013; Kern &
Friedman, 2008). Furthermore, the Big Five personality traits
assessed in childhood, childhood Conscientiousness and related
traits of self-regulation in particular, predict mortality (Friedman et
al., 1993) and objectively assessed health outcomes later in life
This article was published Online First January 26, 2015.
Sarah E. Hampson, Grant W. Edmonds, and Lewis R. Goldberg, Oregon
Research Institute, Eugene, Oregon; Joan P. Dubanoski and Teresa A.
Hillier, Kaiser Permanente Center for Health Research Hawaii, Honolulu,
Hawaii.
This research was supported by a Grant R01AG20048 from the United
States Department of Health and Human Services, National Institutes of
Health, National Institute on Aging. The authors thank Benjamin P. Chapman, Karen A. Matthews, and Howard Friedman for their comments on a
draft.
Correspondence concerning this article should be addressed to Sarah E.
Hampson, Oregon Research Institute, 1776 Millrace Drive, Eugene, OR
97403-2536. E-mail: [email protected]
887
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888
HAMPSON, EDMONDS, GOLDBERG, DUBANOSKI, AND HILLIER
U.S. Department of Health & Human Services, 2004). There is
ample evidence that personality traits measured in adulthood,
particularly Conscientiousness, are associated with health-related
behaviors, including smoking, physical activity, and eating habits
(Bogg & Roberts, 2004). Studies have also examined health behaviors as mediators of the influence of adult personality on
mortality (e.g., Hagger-Johnson et al., 2012; Hill, Turiano, Hurd,
Mroczek, & Roberts, 2011; Lodi-Smith et al., 2010; Turiano,
Chapman, Gruenewald, & Mroczek, 2013; Turiano, Hill, Roberts,
Spiro, & Mroczek, 2012). As comprehensively reviewed by Turiano et al. (2013), these and other studies of adult personality
traits and health outcomes show varying degrees of support for
health-behavior mechanisms.
Studies of health-behavior mechanisms to account for the association between childhood personality and adult health outcomes
are rare (Friedman et al., 1995; Martin, Friedman, & Schwartz,
2007). The leading causes of mortality, such as heart disease and
diabetes, develop over decades and are associated with healthdamaging behavior patterns including smoking, physical inactivity, and poor diet. We theorized that childhood Conscientiousness
influences adult health outcomes by directing an individual onto
enduring pathways of more or less healthful behaviors that have
cumulative effects on health over time. That is, health outcomes
should be worse for individuals who have had greater lifetime
exposure to smoking, inactivity, and excessive calorie consumption. A limitation of much of the previous work investigating
health-behavior mechanisms is the lack of measures that capture
accumulation of multiple behaviors over time. In the present study,
we partially rectified this by using a cumulative index composed of
retrospective reports of these behaviors over previous periods of
the life span. Because we suspect that health behaviors have
cumulative effects over time, and childhood Conscientiousness is
likely to influence these, we further theorized that child Conscientiousness is a stronger predictor of adult health status than is
adult Conscientiousness. That is, we predicted lasting effects of
child Conscientiousness on adult health that would only be partially, if at all, superseded by later influences from adult Conscientiousness.
The present study examined a “chain-of” influence model (Shanahan, Hill, Roberts, Eccles, & Friedman, 2014) in which health behaviors reportedly performed over decades were hypothesized to explain
the association between childhood personality and later health status.
In addition to using a retrospective, cumulative measure of life-span
health-damaging behavior, this study is novel in several other important respects that addressed limitations of previous work. It is one of
very few studies with both child and adult personality and objectively
assessed adult health outcomes. This study also included two other
major influences on health outcomes, namely educational attainment
and adult cognitive ability. Both are associated with childhood personality (Duckworth, Quinn, & Tsukayama, 2012; Lönnqvist,
Vainikainen, & Verkasalo, 2012), as well as health and longevity
(Calvin et al., 2011; Deary, Weiss, & Batty, 2010; Hagger-Johnson,
Shickle, Deary, & Roberts, 2010), and are therefore likely to affect the
development of health-enhancing or health-damaging behaviors over
the life span.
The model was tested using data from the Hawaii Longitudinal
Study of Personality and Health (Hampson, Goldberg, Vogt, &
Dubanoski, 2006). Previously, it was reported for this sample that
childhood Conscientiousness was the only Big Five trait to be
associated with objectively assessed cardiovascular and metabolic
health over 40 years later, even after controlling for adult Conscientiousness (Hampson et al., 2013). The present study builds on
this finding to investigate a possible life-span health-damaging
behavior mechanism underlying the association between childhood Conscientiousness and objectively assessed physiological
dysregulation in adulthood (a combination of cardiovascular and
metabolic biomarkers that included systolic and diastolic blood
pressure, lipids, fasting blood glucose, and urine protein). We
hypothesized that lower childhood Conscientiousness predicts
higher levels of health-damaging behavior across the life span, and
that a greater accumulation of life-span health-damaging behavior
predicts greater adult dysregulation when also allowing for pathways through educational attainment and cognitive ability (see
Figure 1). The influence of childhood Conscientiousness on dysregulation was expected to be greater than that of adult Conscientiousness. On the basis of the established gender differences in
mortality and morbidity, and the gender differences observed here
and in previous findings (Hampson et al., 2013; Hampson et al.,
2006), we tested this model separately for men and women on an
exploratory basis.
Method
Participants and Procedures
Timeline. Between 1959 and 1967, teachers in entire
elementary-school classrooms on two Hawaiian islands assessed
children on their personality traits toward the end of the school
year one time for each child. In 1998, efforts to find these children,
now middle-aged adults, were begun. When each member of the
original cohort was located (i.e., rolling recruitment), he or she was
invited to join the study. Since joining, participants have completed one or more of six questionnaires (Q1–Q6) and, from 2003
onward, have been invited to attend a half-day medical and psychological examination. In addition to the childhood personality
assessment, measures used here were drawn from items in Q1
(adult personality, smoking, educational attainment), Q3 (smoking, physical activity and inactivity), and Q4 (BMI), and the clinic
visit (cognitive ability, physiological dysregulation). On average,
Q3 was completed 5.4 years after Q1 (SD ⫽ .40, range ⬍1–7.5
years), and Q4 was administered 2 years after Q3. The clinic visit
occurred 1.2 years after Q3 (SD ⫽ 2.2, range ⫽ ⫺2.7–7.3 years).
Sample. Of the 2,418 in the original child cohort, 79 were
already deceased and 19 only had first names recorded, leaving
2,320 to locate. Of these, 1,938 (84%) have been found. Among
those found, 36 immediately refused further contact and one was
illiterate, reducing the potential sample to 1,901. Of these, 1,387
(73%) have been recruited and have completed at least one questionnaire. To be included in the subsample for this report, participants had to have participated in the medical and psychological
examination at 51 years, and to have completed the first questionnaire. Five participants were excluded because of substantial differences in the traits used in their childhood personality assessment
at their school. These requirements limited the eligible subsample
to 372 men and 387 women (N ⫽ 759).
Compared with participants who provided demographic information on the first questionnaire or by phone, but did not attend the
medical and psychological examination (n ⫽ 622), this subsample
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LIFE-SPAN BEHAVIORAL MECHANISM
889
Figure 1. Hypothesized initial model from childhood Conscientiousness to dysregulation including indirect
paths through life span health-damaging behaviors, educational attainment and adult cognitive ability, with life
span health-damaging behaviors and adult cognitive ability allowed to correlate.
included more Japanese Americans (35% vs. 28%), fewer Caucasians (16% vs. 24%) and Native Hawaiians or other Pacific Islanders (19% vs. 25%), and more “other” ethnicities (30% vs.
23%). They also had higher educational attainment (M ⫽ 6.88 vs.
6.57), but did not differ on any of the childhood Big Five traits.
Measures
Childhood personality. For the children in the present sample, teachers assessed their entire elementary school classrooms
(Grades 1, 2, 5, or 6; M age ⫽ 10 years) by rank-ordering children
on each of a comprehensive set of 43– 49 personality attributes,
which included 39 items common to all children, using a 9-step
quasi-normal distribution. Definitions developed by teachers for
each attribute were provided. Orthogonal factor scores (standard
scores) for the Big Five were derived for subgroups of children
who were rated on the same set of attributes (Goldberg, 2001).
Mean ␣ reliabilities across subgroups for these factor scores (Ten
Berge & Hofstee, 1999) were as follows: .75 (Extraversion), .62
(Agreeableness), .77 (Conscientiousness), .68 (Emotional Stability), and .60 (Intellect/Imagination; Edmonds, Goldberg, Hampson, & Barckley, 2013). The validity of these childhood measures
as predictors of adult outcomes has been demonstrated in previous
studies (e.g., Goldberg, 2001; Hampson et al., 2006; Hampson,
Goldberg, Vogt, & Dubanoski, 2007; Woods & Hampson, 2010).
Adult personality traits. The first questionnaire included the
44-item Big Five Inventory (John & Srivastava, 1999). Participants rated the self-descriptiveness of each item (1 ⫽ very inaccurate, 5 ⫽ very accurate). Alpha reliabilities for this measure for
the Hawaii cohort are as follows: .84 (Extraversion), .78 (Agreeableness), .80 (Conscientiousness), .82 (Emotional Stability), and
.79 (Intellect/Openness; Edmonds et al., 2013).
Life-span health-damaging behaviors: Smoking, physical inactivity, and obesity. Smoking history was assessed by items from
Q1 and Q3. Where participants reported never smoking on Q1 but
provided a smoking history on Q3 (n ⫽ 60), their latter responses
were used. Ever smokers (at least 100 cigarettes in their entire life)
were asked the age when they started smoking regularly, whether
they smoked now, and if so, how much they smoked per day.
Ex-smokers were asked their ages when they first started smoking,
their ages when they quit, and on average how much they smoked
per day over all the years they smoked. Life-time smoking history
was coded as 0 ⫽ ⱕ100 cigarettes, 1 ⫽ previously smoked ⬍8
pack years, 2 ⫽ previously smoked ⱖ8 pack years, 3 ⫽ currently
smoke (in last year) ⱕ1/2 a pack per day, 4 ⫽ currently smoke (in
last year) ⱖ1 pack a day. A pack year, derived from participants’
smoking histories, was defined as the equivalent of smoking one
pack a day for one year. The median number of pack years for
ex-smokers was 8. This measure assessed the extent of previous
smoking among ex-smokers, as well as the extent of smoking
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890
HAMPSON, EDMONDS, GOLDBERG, DUBANOSKI, AND HILLIER
among current smokers to better capture lifetime cigarette exposure.
Cumulative physical inactivity over the life span was assessed by separate questions on Q3 asking participants to check
the time periods when they “engaged in no exercise and were
quite inactive,” as well as the time periods when they “engaged
in sports or were otherwise quite physically active.” For each
question, they checked as many of the following 10 periods as
applied: before entering school, during elementary school, during junior high, during high school, from age ranges 18 –25,
26 –30, 31–35, 36 – 40, 41– 45, and age 46 onward. The sum of
periods of physical inactivity minus the sum of periods of
activity was calculated to create a cumulative physical inactivity score (maximum score ⫽ 10).
Body mass index (BMI; kg/m2) across adult life was assessed on
Q4 by self-reported height and weight at ages 20, 30, and 40.
Height reported for one age was assumed to be the same if missing
for others. Where height or weight was missing, BMI was imputed
from other items assessing obesity, which were less often missing.1 The sum of BMI across ages 20, 30 and 40 was used as a
cumulative measure of obesity. Using a sum versus a mean would
make no difference to correlations or betas in the analytic model.
The sum of the three time periods was used to reflect the concept
of cumulative exposure to the health-damaging effects of obesity.
Missing data on components of the summative variables of physical inactivity or BMI would potentially underestimate lifetime
exposure to these variables, thus operating against our hypotheses.
Although not a direct measure of quantity or quality of food intake,
obesity has been used as an indicator of behaviors conducive to
weight gain in previous comparable longitudinal studies (Friedman
et al., 1993; Turiano et al., 2013). Retrospective dietary recall over
the life span was deemed impractical and error prone.
Smoking behavior, physical inactivity, and BMI across the life
span were not highly intercorrelated (smoking and BMI: r ⫽ .11;
smoking and physical inactivity: r ⫽ ⫺.04; BMI and physical
inactivity r ⫽ ⫺.05). We reasoned that greater accumulated exposure to one or more of these behaviors would have negative
consequences for health. Each measure was z-scored for men and
women combined and the three measures were summed to form an
index of accumulated exposure to health-damaging behaviors
across the life span (higher scores indicated more unhealthy behavior).
Clinical indicators of health status. A composite measure of
dysregulation was formed from the following cardiovascular and
metabolic biomarkers: systolic and diastolic blood pressure (means
of two assessments), total cholesterol/HDL ratio, HDL (reversed),
fasting triglycerides, fasting blood glucose, and urine protein (log
transformed). Previously, we included obesity and medication
taking in this measure (Hampson et al., 2013; Hampson, Goldberg,
Vogt, Hillier, & Dubanoski, 2009). These two components were
removed from the present measure because they can both be
construed as health behaviors, one of the hypothesized mediators
in this study: obesity is a proxy for diet, and medication taking is
a proxy for treatment seeking and adherence.2 Moreover, obesity
to age 40 (as a proxy for diet) was included in the measure of
lifetime health behaviors. A participant’s dysregulation score was
derived by standardizing each measure across men and women and
summing the standard deviations from the mean. There were nine
participants who were missing either one or two measures. In an
earlier investigation of dysregulation, we allowed for the possibility of curvilinear models for some components of dysregulation in
which both extreme high and low scores were associated with poor
health. Across the indicators of dysregulation, few (1–2%) participants fell in the very low, unhealthy range (Hampson et al., 2009).
This justified treating dysregulation as a linear gradient on which
higher scores indicated poorer health, and low scores indicated
better overall health.
Educational attainment. Participants checked their highest
level of educational attainment ranging from 1 ⫽ eighth grade or
less to 9 ⫽ postgraduate or professional degree.
Adult cognitive ability. Three domains of cognitive ability
were assessed using tests from the Woodcock Johnson III battery
(Woodcock, Mather, & McGrew, 2001): Verbal Comprehension
(picture vocabulary, synonyms, antonyms, analogies), Concept
Formation (identifying the dimensions on which two sets of drawn
objects differ), and Timed Visual Matching (finding pairs of identical numbers in strings of numbers). These three domains were
used as indicators for a latent construct of cognitive ability.
Results
Means and standard deviations for men and women on all study
variables and significant gender differences are presented in Table
1. In childhood, women were viewed by their teachers as less
extraverted, more conscientious, and less emotionally stable as
children than were men. As adults, women had higher cognitive
ability and less dysregulation than men. For both genders, the only
childhood personality trait to correlate with dysregulation was
Conscientiousness. The only adult trait to correlate with dysregulation was adult Conscientiousness for women (r ⫽ ⫺.11). The
correlations among all the study variables are shown in Table 2.
Residualized change scores for Conscientiousness (regressing
adult scores on child scores) were not significantly correlated with
dysregulation for men (r ⫽ .05) or women (r ⫽ ⫺.08), indicating
that change in Conscientiousness from child to adult did not
account for additional variance beyond the child trait, which is
consistent with the modest stability of Conscientiousness from
childhood to adulthood for this cohort (r ⫽ .25; Edmonds et al.,
2013).
Figure 1 shows the hypothesized directional and correlational
paths tested in the initial model. Adult cognitive ability and lifespan health-damaging behavior were allowed to correlate because
adult cognitive ability could not have influenced health behaviors
reportedly performed decades earlier. Adult Conscientiousness
was allowed to correlate with life-span health-damaging behaviors
and adult cognitive ability. Model testing was conducted using
Mplus Version 7.0 (Muthén & Muthén, 1998-2012) with maxi1
Other weight items were comparison of weight to peers (1 ⫽ much
lighter, 5 ⫽ much heavier), self-reported waist size, and body type (Bhuiyan, Gustat, Srinivasan, & Berenson, 2003) at ages 20, 30, and 40.
Separately by gender, BMI was predicted for cases with valid measures of
BMI, and those regression weights were applied to the valid predictors to
compute the missing BMI. Fewer than 8% of cases were imputed, and the
means with the imputed values included were within .05 of the means
before imputing.
2
Including medication use as a predictor of dysregulation made no
appreciable difference to the pattern of results reported here.
LIFE-SPAN BEHAVIORAL MECHANISM
891
Table 1
Descriptive Statistics for Men and Women
Men (n ⫽ 372)
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Variable/Factor
Age (in years) at clinic examination
Educational attainment (1 ⫽ ⱕ 8th grade,
9 ⫽ postgraduate)
Childhood personality
Extraversion
Agreeableness
Conscientiousness
Emotional Stability
Intellect/Openness
Cognitive ability
Life-span health-damaging behavior
Dysregulation
Women (n ⫽ 387)
Mean (SD)
Cohen’s d
51.57 (2.78)
51.49 (2.82)
.03
6.83 (1.82)
6.93 (0.77)
.06
.14 (.96)
⫺.05 (.98)
⫺.24 (1.00)
.09 (.97)
.10 (1.08)
⫺.14 (.86)
⫺.05 (1.76)
.18 (.55)
⫺.05 (1.01)
.09 (.99)
.43 (.88)
⫺.10 (1.00)
.03 (.92)
.11 (.76)
⫺.04 (1.73)
⫺.18 (.53)
.20ⴱ
.14
.71ⴱ
.19ⴱ
.08
.30ⴱ
.01
.68ⴱ
Note. Childhood personality, life-span health-damaging behaviors, cognitive ability, and dsysregulation are in standard scores. Significant differences
between men and women are shown.
ⴱ
p ⬍ .05.
mum likelihood estimation for missing data.3 Model fit was evaluated by the chi-square statistic and, because it is sensitive to
sample size, it was supplemented by the two-index approach
recommended by Hu and Bentler (1999), namely, the root mean
square error of approximation (RMSEA) and the comparative fit
index (CFI). They suggested cutoffs of .06 for RMSEA and .95 for
CFI for excellent fit, and statistics close to these cutoffs are
considered acceptable. While retaining the direct path from childhood Conscientiousness to adult dysregulation, other hypothesized
but nonsignificant paths were removed sequentially, starting with
the least significant path first. Using this trimmed model, we tested
the significance of all indirect paths using a bootstrapping method
within Mplus (Bollen & Stine, 1990; Shrout & Bolger, 2002).
The final models provided support for a cumulative healthbehavior mechanism (see Figures 2a for men and 2b for women.
The models accounted for 7.4% of the variance in dysregulation
for women and 16.5% of the variance in dysregulation for men.
For both genders, childhood Conscientiousness predicted adult
Conscientiousness, but adult Conscientiousness did not predict any
other variables in the model. In addition, childhood Conscientiousness predicted life-span health-damaging behaviors through educational attainment, and life-span health-damaging behaviors predicted dysregulation. Thereafter, the indirect effects differed
across the models for men and women (see Table 3). In the model
for men, higher childhood Conscientiousness was associated with
less dysregulation through less health-damaging behavior. Educational attainment was also involved in predicting health behavior
and dysregulation: Consistent with a chain of influence, the indirect path from childhood Conscientiousness to dysregulation
through educational attainment and health-damaging behaviors
was significant. Men’s cognitive ability did not predict dysregulation, but a significant direct path from educational attainment to
dysregulation was retained in the model.
For women, the indirect path from childhood Conscientiousness
to dysregulation through educational attainment and healthdamaging behaviors was not significant. However, the indirect
effect of Conscientiousness on dysregulation through cognitive
ability was significant: Higher Conscientiousness was related to
higher educational attainment, which was associated with greater
cognitive ability, which was associated with less dysregulation.
Discussion
This study examined a cumulative life-span health-behavior
mechanism to account for associations between childhood Conscientiousness and adult health status. The primary finding was that
the models for both men and women included paths between
constructs suggestive of a chain of influence from childhood
Conscientiousness through life-span health-damaging behaviors to
adult dysregulation. Our findings suggest that the association between childhood Conscientiousness and mortality found in previous studies could be explained in part by cumulative behavioral
mechanisms leading to poorer health in adulthood that might
impact longevity. A test of this complete pathway will eventually
be possible with the Hawaii cohort.
The indirect path from childhood Conscientiousness to healthdamaging behavior through educational attainment was significant
for both genders, as was the path from health-damaging behavior
to dysregulation. The entire indirect path from childhood Conscientiousness through educational attainment and health-damaging
behaviors to dysregulation was significant for men but not women.
Men in this sample had higher mean levels of dysregulation than
women, indicating that they were in poorer cardiovascular and
metabolic health. On average, women develop cardiovascular disease 10 or more years later than men (Rossouw, 2002), so it is
possible that the entire indirect effect for women will become
stronger after an additional 10 years of cumulative life-span
health-damaging behaviors as well as when their cardiovascular
and metabolic health has deteriorated further. The 10-year
3
Educational attainment was missing for 60 participants, and six were
missing cognitive ability. Scores on all three components of lifespan
health-damaging behavior were required resulting in 301 missing cases.
When the trimmed models were rerun excluding these160 men and 141
women, the path coefficients were comparable in size and sign (see online
supplementary materials).
HAMPSON, EDMONDS, GOLDBERG, DUBANOSKI, AND HILLIER
892
Table 2
Correlations Among All Constructs in the Model, Women Above the Diagonal and Men Below
the Diagonal
Variable
1.
2.
3.
4.
5.
6.
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ⴱ
Child Conscientiousness
Adult Conscientiousness
Educational attainment
Cognitive ability
Life-span health-damaging behavior
Dysregulation
p ⬍ .05.
ⴱⴱ
1
.24ⴱⴱ
.16ⴱⴱ
.11ⴱ
⫺.20ⴱⴱ
⫺.10ⴱ
2
.15ⴱⴱ
.11ⴱ
.05
⫺.14ⴱ
.03
3
.16ⴱⴱ
.09
.60ⴱⴱ
⫺.27ⴱ
⫺.23ⴱⴱ
4
.23ⴱⴱ
.09
.55ⴱⴱ
⫺.27ⴱⴱ
⫺.15ⴱⴱ
5
6
⫺.11
⫺.16ⴱ
⫺.28ⴱⴱ
⫺.22ⴱⴱ
⫺.13ⴱ
⫺.11ⴱ
⫺.18ⴱⴱ
⫺.15ⴱⴱ
.20ⴱⴱ
.33ⴱⴱ
p ⬍ .01.
follow-up clinical health assessment at mean age 61 that has just
begun for the Hawaii cohort will enable us to test this possibility.
The present findings suggest that educational attainment is an
important element in life-span behavioral pathways to health status. It is well-established that higher levels of education reduce the
likelihood of health-damaging behaviors such as smoking (Pampel, Krueger, & Denney, 2010), and education may increase
knowledge and understanding of health-enhancing behaviors and
their importance for disease prevention and management. Better
educated individuals may be more likely to recognize disease
symptoms and to obtain medical care (Glied & Lleras-Muney,
2008; Gottfredson, 2004), and to enjoy other benefits of higher
socioeconomic status, which may also account for the direct effect
of educational attainment on dysregulation for men.
The present study also suggests the importance of cognitive
ability for pathways from personality to health. For women, but
not men, childhood Conscientiousness predicted dysregulation
through educational attainment and cognitive ability. This finding
for women is consistent with a previous study of adults, in which
cognitive ability partially mediated the effects of adult Conscientiousness on mortality (Hill et al., 2011). However, it is not clear
why the model for men did not show a comparable effect.
The present study also has broader implications for life-span
research on personality and health. Socioeconomic disparities in
Figure 2. (a) Path diagram showing standardized factor loading and regression weights for the trimmed model
from men’s childhood Conscientiousness to adult dysregulation (N ⫽ 372). Fit statistics for the trimmed model:
␹2 ⫽ 22.83, df ⫽ 11, p ⫽ .02, RMSEA ⫽ .05, 90% CI ⫽ .02, .08, CFI ⫽ .98; for the initial model: ␹2 ⫽ 19.07,
df ⫽ 9, p ⫽ .02, RMSEA ⫽ .06, 90% CI ⫽ .02, .09, CFI ⫽ .98. (b) Path diagram showing standardized factor
loading and regression weights for the trimmed model from women’s childhood Conscientiousness to adult
dysregulation (N ⫽ 387). Fit statistics for the trimmed model: ␹2 ⫽ 26.78, df ⫽ 13, p ⫽ .01, RMSEA ⫽ .05,
90% CI ⫽ .02, .08, CFI ⫽ .98; for the initial model: ␹2 ⫽ 21.48, df ⫽ 9, p ⫽ .01, RMSEA ⫽ .06, 90% CI ⫽
.03, .09, CFI ⫽ .98.
LIFE-SPAN BEHAVIORAL MECHANISM
Table 3
Standardized Direct and Indirect Effects
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Indirect path
Men
C ¡ Adult C
C ¡ EA
C ¡ LHDB
EA ¡ LHDB
EA ¡ Cognitive ability
EA ¡ Dysreg
LHDB ¡ Dysreg
C ¡ EA ¡ LHDB
C ¡ LHDB ¡ Dysreg
C ¡ EA ¡ LHDB ¡ Dysreg
C ¡ EA ¡ Dysreg
Women
C ¡ Adult C
C ¡ EA
EA ¡ LHDB
EA ¡ Cognitive ability
LHDB ¡ Dysreg
Cognitive ability ¡ Dysreg
C ¡ EA ¡ LHDB
C ¡ EA ¡ Cognitive ability ¡
Dysreg
C ¡ EA ¡ LHDB ¡ Dysreg
Effect
p value
95% CI
.238
.170
⫺.181
⫺.256
.697
⫺.123
.352
⫺.043
⫺.064
⫺.015
⫺.021
.000
.001
.003
.000
.000
.027
.000
.016
.029
.046
.086
.140, .336
.070, .270
⫺.299, ⫺.181
⫺.383, ⫺.128
.632, .763
⫺.232, ⫺.014
.216, .488
⫺.080, ⫺.007
⫺.120, ⫺.007
⫺.030, ⫺.000
⫺.043, .001
.145
.178
⫺.292
.662
.179
⫺.137
⫺.052
.004
.000
.000
.000
.004
.011
.006
.046, .244
.079, .276
⫺.408, ⫺.292
.592, .732
.057, .301
⫺.243, ⫺.032
⫺.089, ⫺.015
⫺.016
⫺.009
.012
.134
⫺.029, ⫺.004
⫺.021, .003
Note. C ⫽ childhood Conscientiousness; Adult C ⫽ adult Conscientiousness; EA ⫽ educational attainment; LHDB ⫽ life-span health-damaging
behavior; Dysreg ⫽ dysregulation.
mortality disappear by the time people reach their 80s, presumably
because by this age, prevention and treatment cannot delay inevitable biological aging (Phelan, Link, Diez-Roux, Kawachi, &
Levin, 2004). A comparable question could be asked regarding
disparities relating to personality traits (Shanahan et al., 2014). At
what age do health advantages accruing to those with higher
Conscientiousness no longer hold? Our results suggest that childhood Conscientiousness continues to confer health advantages at
least up to the 50s. Adult Conscientiousness did not predict dysregulation beyond childhood Conscientiousness. Change in Conscientiousness had no effects on health in the present study, but the
association between personality change over shorter periods and
health outcomes should be examined in future research. Traits in
childhood may have long-lasting consequences by directing individuals onto paths to adult development that include educational
attainment, maintenance of cognitive ability, and habitual behaviors. In this way, the downstream effects of childhood personality
can be independent of adult personality traits, which are only
modestly correlated (at best) with childhood traits over time spans
as long at 40 years (Edmonds et al., 2013). In future research, it
would be useful to determine the generality of the present findings,
but few studies have assessments of childhood personality, adult
personality, and health outcomes. It would be valuable to learn
more about how the pathways from early personality to later health
are established, for example by examining child or adolescent
personality influences on the formation and maintenance of health
habits.
Inevitably, this study has limitations. The measure of life-span
health-damaging behaviors was limited to smoking, physical inactivity, and BMI. Other important health behaviors to include
would be alcohol and other substance use and health-care utiliza-
893
tion, but these lifetime data were not available for this cohort. BMI
is only an indirect measure of behaviors related to an imbalance
between caloric intake versus expenditure, and gives no indication
of quantity or quality of food intake. More direct measures of
dietary habits would be preferable. BMI is also somewhat confounded with physical activity. Ideally, health behaviors would be
measured at regular time points across the life span instead of
retrospectively. The retrospective index only approximated a measure of accumulating risk over the life span. Cognitive ability was
first assessed at mean age 51 in this cohort. Because educational
attainment is typically achieved before this age, we placed educational attainment as causally prior to cognitive ability in our
models. Although cognitive ability remains relatively stable across
the life span, the direction of association between educational
attainment and ability is likely to be reciprocal and dependent on
many other contextual factors (Deary et al., 2010). Treating ability
at age 51 as the consequence of educational attainment remained
faithful to the temporal ordering of the assessment of these variables in this study, as did the likelihood that educational attainment
is completed well before age 51 for most people, but may have
oversimplified the actual association between them. With only one
assessment of health outcomes, it was not possible to determine
when in the life span the effects of cumulative health-damaging
behaviors can be first observed. This information would be valuable for identifying optimal time points for interventions, and for
the further investigation of the likely complex and reciprocal
relations among personality, health behaviors, and health in adulthood. The childhood personality assessment preceded the adult
assessments by at least 4 decades, but the ordering of the adult
assessments corresponded less well to the temporal hypotheses.
Only modest amounts of variance were accounted for by the
models, and the indirect effects were small. It is important to keep
in mind the size of the raw bivariate correlation between childhood
Conscientiousness and dysregulation (r ⫽ ⫺.13 and ⫺.10 for
women and men, respectively), which necessarily limits the size of
indirect effects. Numerous factors other than those studied here
have influenced health outcomes over 40 years. Seen in this light,
the identification of any significant indirect effects over such a
long period is remarkable. Despite calls for research on life-span
mechanisms to explain associations between personality and
health (Friedman, 2000; Hampson & Friedman, 2008; Smith,
2006), there have been few studies to attempt this. The present
study identified modest indirect effects pointing to possible underlying life-span mechanisms, which may be seen as a valuable
initial contribution to this sparse literature.
Despite these and other limitations, the main novel contribution
made by this study to the field of personality and health has been
to investigate a life-span behavioral mechanism that unfolds over
time periods measured in decades, not months. Future longitudinal
studies will shed more light on the complex processes linking
personality to subsequent health outcomes. Investigating pathways
linking childhood personality with later biomarkers of cardiovascular and metabolic health may identify opportunities to disrupt
unhealthy trajectories leading to morbidity and mortality.
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Received June 9, 2014
Revision received December 1, 2014
Accepted December 13, 2014 䡲